paddle.v2.fluid.layers.dynamic_gru(input, size, param_attr=None, bias_attr=None, is_reverse=False, gate_activation='sigmoid', candidate_activation='tanh', h_0=None)Dynamic GRU Layer
+Refer to Empirical Evaluation of Gated Recurrent Neural Networks on +Sequence Modeling
+The formula is as follows:
+The \(\odot\) is the element-wise product of the vectors. \(act_g\) +is the update gate and reset gate activation function and \(sigmoid\) +is usually used for it. \(act_c\) is the activation function for +candidate hidden state and \(tanh\) is usually used for it.
+Note that these \(W_{ux}x_{t}, W_{rx}x_{t}, W_{cx}x_{t}\) operations on +the input \(x_{t}\) are NOT included in this operator. Users can choose +to use fully-connect layer before GRU layer.
+| Parameters: |
|
+
|---|---|
| Returns: | The hidden state of GRU. The shape is (T times D), and lod is the same with the input. + |
+
| Return type: | Variable + |
+
Examples
+hidden_dim = 512
+x = fluid.layers.fc(input=data, size=hidden_dim * 3)
+hidden = fluid.layers.dynamic_gru(input=x, dim=hidden_dim)
+IfElse Operator","Design Doc: InferVarType","Problem","Memory Optimization","Intel\u00ae MKL Packed on PaddlePaddle: Design Doc","Intel\u00ae MKL-DNN on PaddlePaddle: Design Doc","Design Doc: Add MKLDNN Kernel in Fluid Operator","Design Doc: Model Format","Paddle\u591a\u8bed\u8a00\u63a5\u53e3\u5b9e\u73b0","C-API \u6a21\u578b\u63a8\u65ad\u5b9e\u73b0\u6587\u6863","Design Doc: The Keys of Operator Kernel Type","RNNOp design","Design: Sequence Decoder Generating LoDTensors","Optimizer Design","Design Doc: NCCL support in Paddle Fluid","Averaging Parameter in PaddlePaddle","Design Doc: The C++ Class Parameters","Introduction","Design Doc: PaddlePaddle Programs","Prune","Design Doc: Python API","Python Data Reader Design Doc","Design Doc: Refactorization Overview","Design Doc: Gradient Operators Registration","Regularization in PaddlePaddle","PaddlePaddle\u53d1\u884c\u89c4\u8303","Design of Scope in Paddle","Design Doc: Selected Rows","Interaction between C++ and Python","Design Doc: Supporting new Device/Library","Background","Design for TensorArray","Background","Build from Sources","Run in Docker Containers","Install and Build","Install Using pip","GET STARTED","RNN Models","RNN Configuration","Build using Docker","Contribute Code","Write New Layers","How to write a new operator","Add Kernels for a New Device","How to use Eigen in Paddle","Contribute Documentation","HOW TO","Profiling the Python Code","Tune GPU Performance","PaddlePaddle Fluid Source Code Overview","Distributed Training","Cluster Training Using Fabric","Fluid Distributed Training","Distributed PaddlePaddle Training on AWS with Kubernetes","PaddlePaddle On Kubernetes","Cluster Training Using OpenMPI","<no title>","<no title>","Argument Outline","Detail Description","Set Command-line Parameters","Use Case","PaddlePaddle Documentation","Build PaddlePaddle for Android","Build PaddlePaddle for iOS","Build PaddlePaddle for Raspberry Pi","MOBILE","Cluster bootstrapping tool 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volum:110,vpc:110,warp_ctc:4,weightdecayregular:23,what:[34,38,96,105],when:[38,82],whl:92,why:[49,50,71,77,78,87,105],wmt14:10,worker:40,workflow:97,wrapper:98,write:[97,98,99,100,102],www:102,xavieriniti:16,yaml:111,your:[90,100],zero:18}})
\ No newline at end of file
diff --git a/develop/doc_cn/_sources/api/v2/fluid/layers.rst.txt b/develop/doc_cn/_sources/api/v2/fluid/layers.rst.txt
index 550b0e5b82609750ccd318eee889313cb2d7925a..f873c93d9a3424497c089fa7ee44122856090610 100644
--- a/develop/doc_cn/_sources/api/v2/fluid/layers.rst.txt
+++ b/develop/doc_cn/_sources/api/v2/fluid/layers.rst.txt
@@ -18,6 +18,11 @@ dynamic_lstm
.. autofunction:: paddle.v2.fluid.layers.dynamic_lstm
:noindex:
+dynamic_gru
+-----------
+.. autofunction:: paddle.v2.fluid.layers.dynamic_gru
+ :noindex:
+
data
----
.. autofunction:: paddle.v2.fluid.layers.data
diff --git a/develop/doc_cn/api/v2/fluid/layers.html b/develop/doc_cn/api/v2/fluid/layers.html
index f32f2df104325953580b2f9793017cff20c703ac..fa6ded1ac52524aadd082d7bcf6a15ad665ecfe0 100644
--- a/develop/doc_cn/api/v2/fluid/layers.html
+++ b/develop/doc_cn/api/v2/fluid/layers.html
@@ -468,6 +468,74 @@ default “tanh”.
paddle.v2.fluid.layers.dynamic_gru(input, size, param_attr=None, bias_attr=None, is_reverse=False, gate_activation='sigmoid', candidate_activation='tanh', h_0=None)Dynamic GRU Layer
+Refer to Empirical Evaluation of Gated Recurrent Neural Networks on +Sequence Modeling
+The formula is as follows:
+The \(\odot\) is the element-wise product of the vectors. \(act_g\) +is the update gate and reset gate activation function and \(sigmoid\) +is usually used for it. \(act_c\) is the activation function for +candidate hidden state and \(tanh\) is usually used for it.
+Note that these \(W_{ux}x_{t}, W_{rx}x_{t}, W_{cx}x_{t}\) operations on +the input \(x_{t}\) are NOT included in this operator. Users can choose +to use fully-connect layer before GRU layer.
+| 参数: |
|
+
|---|---|
| 返回: | The hidden state of GRU. The shape is (T times D), and lod is the same with the input. + |
+
| 返回类型: | Variable + |
+
Examples
+hidden_dim = 512
+x = fluid.layers.fc(input=data, size=hidden_dim * 3)
+hidden = fluid.layers.dynamic_gru(input=x, dim=hidden_dim)
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